# Copyright (C) 2022 The Qt Company Ltd.
# Contact: https://www.qt.io/licensing/
#
# You may use this file under the terms of the CC0 license.
# See the file LICENSE.CC0 from this package for details.

import io
import os
import zipfile

import requests


def partially_hide(x):
    words = []
    x_split = x.split()
    len_split = len(x_split)

    for i, name in enumerate(x_split):
        # Replace with dots
        # filled = '.' * (len(name) - 1)
        # words.append(f'{name[0]}{filled}')

        # Use first letter
        # words.append(name[0])

        # User F. Lastime
        if i != len_split - 1:
            words.append(f"{name[0]}.")
        else:
            words.append(name)
    return " ".join(words)


def get_domain_chart_data(df):
    d = df.groupby("domain")["domain"].count()
    d = d.to_frame()
    d.rename(columns={"domain": "domain_count"}, inplace=True)
    d = d.sort_values(by="domain_count", ascending=False)
    TOP = 5
    d3 = d[:TOP].copy()
    d3.loc["Other"] = d[TOP:]["domain_count"].sum()
    d3 = d3.iloc[::-1]
    total = d3["domain_count"].sum()
    p = (d3["domain_count"] / total) * 100

    return {
        "data": [
            {
                "x": d3["domain_count"],
                "y": [f"{i} " for i in d3.index],
                "text": p,
                "type": "bar",
                "orientation": "h",
                # "marker": {"color": "#f9e56d"},
                "marker": {"color": "#41CD52"},
                "texttemplate": "%{value} (%{text:.2f} %)",
                "textposition": "auto",
            },
        ],
        "layout": {
            "title": "Commits per email domain",
            "height": "400",
            "padding": {
                "r": "150",
            },
        },
    }


def get_ranking_chart_data(df, top=10, column="commit_count"):
    d4 = (
        df.groupby("name")
        .agg({"name": "count", "files_changed": "sum", "insertions": "sum", "deletions": "sum"})
        .rename(columns={"name": "commit_count"})
    )
    d4 = d4.sort_values(by=column, ascending=False)[:top]
    d4 = d4.reset_index()
    d4["name"] = d4["name"].apply(partially_hide)
    d4 = d4.iloc[::-1]

    titles = {
        "files_changed": "Files changed",
        "commit_count": "Commits",
        "insertions": "Insertions",
        "deletions": "Deletions",
    }

    colors = {
        "files_changed": "#53586b",
        "commit_count": "#222840",
        "insertions": "#41CD52",
        "deletions": "#fb6761",
    }

    return {
        "data": [
            {
                "y": d4["name"],
                "x": d4[column],
                "type": "bar",
                "name": "Commits",
                "orientation": "h",
                "marker": {"color": colors[column]},
            },
        ],
        "layout": {
            "title": f"Contributors ({titles[column]})",
            "yaxis": {"dtick": "1"},
            "bargap": "2",
            "margin": {
                "l": "100",
            },
        },
    }


def get_commit_chart_data(df):
    d = df.groupby("date_week")["date_week"].count()
    d = d.to_frame()
    d.rename(columns={"date_week": "date_count"}, inplace=True)
    d = d.reset_index()
    # d["week"] = d["date_week"].copy().apply(lambda x : int(x.split("W")[-1]))
    # d["year"] = d["date_week"].copy().apply(lambda x : int(x.split("W")[0]))

    return {
        "data": [
            {
                "x": d["date_week"],
                "y": d["date_count"],
                "line": {"color": "#222840"},
                "type": "lines",
                "xaxis": "x1",
            },
        ],
        "layout": {
            "title": "Number of commits",
            "height": "400",
            "xaxis": {"tickangle": "45"},
        },
    }


def get_collab_chart_data(df):
    d = df.groupby("date_week")["email"].nunique()
    d = d.to_frame()
    d.rename(columns={"email": "collaborators_count"}, inplace=True)

    return {
        "data": [
            {
                "x": d.index,
                "y": d["collaborators_count"],
                "line": {"color": "#41CD52"},
                "type": "lines",
            },
        ],
        "layout": {
            "title": "Number of contributors",
            "height": "400",
            "xaxis": {"tickangle": "45"},
        },
    }


# Download the data from an external source which runs a cronjob
# to keep an updated ZIP file with the processed data.
# Heroku will restart every day, so the data will be updated on
# a daily basis.
def download_data():
    print("Downloading data")
    r = requests.get("https://qtstats.info/data_csv.zip")
    if r.status_code == 404:
        print("Error: Problem downloading the Data")
        return False

    with zipfile.ZipFile(io.BytesIO(r.content)) as z:
        z.extractall(".")
    print("Downloading data: DONE")
    return True